The Interaction Effect of Goal Misalignment and Metaknowledge Distribution on Team Decision Making in Operations and Supply Chain Management

Problem Definition: Strategic decisions concerning the management of manufacturing and service operations are often prepared and executed in teams of multiple functional specialists to reap the proven benefits of internal integration. However, specialists do not only bring in diverse expertise but also diverse goals and unique functional incentive structures. We examine how the misalignment of functional goals and the distribution of ‘knowledge of who knows what’ (metaknowledge) affect self-serving political dynamics and the performance of cross-functional Operations and Supply Chain Management (OSCM) teams.

Academic/Practical Relevance: We contribute to the growing body of research on behavioral OSCM by providing theoretical and practical implications for the design of team integration processes from an organizational politics and group cognition perspective.

Methodology: To test our model, we develop a two-by-two vignette-based social team experiment. Based on a sample of 156 sourcing teams (468 participants), we run a conditional process analysis based on hierarchical linear regression models.

Results: We confirm the expectation that goal misalignment triggers team politics, which impede team performance. Our central contribution is evidence for the (inverse) ‘catalyst effect’ of the distribution of metaknowledge: under goal alignment, centralized metaknowledge (i.e., one well informed team member) leads to catalyzing and coordinating benefits that reduce team politics and enhance team performance. However, under goal misalignment, centralized metaknowledge significantly amplifies team politics, significantly reducing performance via mediation.

Managerial Implications: We provide management with clear design implications regarding how to incentivize and govern their cross-functional OSCM teams in terms of functional goals and the distribution of metaknowledge. Executives should either ex-ante align their functional pillars or, if infeasible, seek to bring together functional representatives with similar levels of information on who knows what to reduce biasing politics.